Retail distribution systems process merchandise at three basic levels of aggregation. The first and most granular level is the individual item unit as packaged for sale to consumers. The second level is the “case”, the container that is filled with item units at the factory, sealed, and then unsealed either at the store when the items are placed onto shelves or at an order-fulfillment center where items are to be picked to fill customer orders. The third level of aggregation is the pallet, onto which multiple cases are stacked for bulk shipping, typically by truck.
By far the most pervasive materials-handling process within any retailer's distribution system is the selective retrieval (“picking”) of merchandise from inventory—either cases or individual item units—to fill orders. Yet, despite a steadily increasing level of automation of various materials-handling processes, order-picking remains a mostly manual and labor-intensive process, generally using some variant of the relatively inefficient “man-to-goods model”.
In high-volume retail channels, the standard ordering unit for store-level replenishment is the case. Case-picking to fill store orders (or “order selection”, as it is usually called) occurs in retail distribution centers (“DCs”). Merchandise arrives at the DC from manufacturers or intermediate suppliers on pallets, each pallet typically containing cases of a single product. The task of the DC is to ship to the stores pallets containing a specified number of cases of many different products. The primary method used to transfer cases from incoming pallets to outgoing pallets is a manual process that has changed little over many decades: single-product pallets are placed at picking locations arranged in opposing rows separated by aisle spaces, and human operators (“selectors”) travel on motorized vehicles through those aisles, building mixed pallets as they go. On board each vehicle are one or more (typically two) pallets, and the job of the selector is to drive the vehicle to a series of single-product pallets and place a specified number of cases of each product on the specified outbound pallets. There have been attempts to use machines to automate case selection, but none has enjoyed significant commercial success to date, and manual case-selection is used in the vast majority of retail distribution centers in operation today.
Picking of individual item-units occurs at various points in retail distribution. For example, DCs that supply stores whose physical size and sales volumes are too small for case-quantity replenishment must ship individual item units. Types of stores that are usually replenished in less-than-case-quantity include convenience, drug, and specialty goods. In addition, there is an ever-increasing demand for item-level picking to fill orders that are delivered directly to end-users or consumers, driven largely by the growth in “e-commerce”, i.e. electronic orders placed from personal computers via the Internet. A variety of “man-to-goods” methods are used to perform item-level picking. In applications where the picking volume is low or the product assortment is limited, the model is very similar to that used in case-level order-selection described above or for that matter by shoppers in a self-service store, with pickers taking containers to item locations to make the picks. In applications with higher volume and wider product assortment, “zone” picking is more typical, with each picker stationed in a designated area, or zone, and responsible for picking all ordered items in that area and placing them into totes that move through the zone on conveyors.
Depending on the application and configuration of the order-fulfillment process, pickers in a typical “man-to-goods” process spend only 15% to 30% of their work time actually picking the items and placing them either on a pallet or in a container and the rest of the time traveling to the picking locations, ensuring that the target pick is the right item, ensuring the right number of items have been picked, or just waiting to perform the next transaction. A number of technologies, such as barcode scanning, voice-direction, and pick-to-light have been developed that improve accuracy and improve productivity of non-travel tasks, but the only way to achieve dramatic improvements in labor efficiency is to use a goods-to-man picking model in which the goods to be picked flow to stationary workstations. There have been efforts to create “goods-to-man” item-picking models, most notably through the use of carousels and automated storage-and-retrieval cranes, but these solutions are typically very expensive and have not been widely adopted.
Of course, by far the most prevalent form of item-picking in retail is that performed by customers shopping in self-service stores—indeed the very term “self-service” refers specifically to the process of customers picking their own orders. There have also been attempts to create a new retail operating model—an automated full-service store—by automating this item-picking process. This operating model would have numerous advantages over the self-service model, as it would enable much more efficient and effective operations by the retailer and would provide a much more enjoyable and time-efficient shopping experience to the customer. Some examples of attempts to create this retail operating model include U.S. Pat. Nos. 3,746,130 and 5,890,136 and 5,595,263 and 5,933,814 and 5,595,264 and 5,186,281. Unfortunately, none of these attempts to automate order-fulfillment in a retail store has been successful, primarily because a material-handling system has never existed that can satisfy the very challenging requirements of this application effectively and affordably.